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Distributed or centralized? Long-term dynamic allocation and maintenance planning of modular equipment to produce multi-product natural gas based on life cycle thinking

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Listed:
  • Hong, Bingyuan
  • Cui, Xuemeng
  • Peng, Donghua
  • Zhou, Mengxi
  • He, Zhouying
  • Yao, Hanze
  • Xu, Yupeng
  • Gong, Jing
  • Zhang, Hongyu
  • Li, Xiaoping

Abstract

With the increasing complexity of the natural gas trading market, enhancing the flexibility of multi-product natural gas production has practical significance for improving the whole life cycle benefits of gas fields. At present, the collaborative relationship between multi-product process optimization and modular equipment has not been studied enough; there is still a lack of integrated model coupling process optimization, modular equipment design, and scheduling optimization. Therefore, this paper utilizes the convenient scheduling technique across multiple blocks and establishes a distributed multi-product natural gas processing model based on life cycle thinking, facilitating the enduring, dynamic configuration and upkeep administration of modular equipment. The established optimization model is formulated to maximize the net present value of profits, allowing for the selection of optimal production strategy for various natural gas products, such as LNG (Liquefied Natural Gas), CNG (Compressed Natural Gas), NG (Natural Gas), mainly including volume distribution, capacity of gas, and installation, utilization, inter-block scheduling, and recovery of modular equipment, etc. Modular equipment within multiple blocks can be dynamically adjusted based on the production status of the gas field and the market demand for multi-product natural gas. By researching actual production cases, the effectiveness and reliability of this approach have been verified. The results indicate that the net present value of the equipment cost is 89 % of the traditional equipment, which significantly improves production system flexibility and economic benefits of the gas field. This study proposes new operational and management ideas for future distributed multi-product production models in gas fields by considering the efficiency of natural gas resource development and utilization, as well as the risk resistance of the multi-product natural gas industry chain.

Suggested Citation

  • Hong, Bingyuan & Cui, Xuemeng & Peng, Donghua & Zhou, Mengxi & He, Zhouying & Yao, Hanze & Xu, Yupeng & Gong, Jing & Zhang, Hongyu & Li, Xiaoping, 2024. "Distributed or centralized? Long-term dynamic allocation and maintenance planning of modular equipment to produce multi-product natural gas based on life cycle thinking," Energy, Elsevier, vol. 288(C).
  • Handle: RePEc:eee:energy:v:288:y:2024:i:c:s0360544223031420
    DOI: 10.1016/j.energy.2023.129748
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    References listed on IDEAS

    as
    1. Fang, Zhenhua & Pan, Zhen & Ma, Guiyang & Yu, Jingxian & Shang, Liyan & Zhang, Zhien, 2023. "Exergoeconomic, exergoenvironmental analysis and multi-objective optimization of a novel combined cooling, heating and power system for liquefied natural gas cold energy recovery," Energy, Elsevier, vol. 269(C).
    2. Hong, Bingyuan & Cui, Xuemeng & Wang, Bohong & Fan, Di & Li, Xiaoping & Gong, Jing, 2022. "Long-term dynamic allocation and maintenance planning of modular equipment to enhance gas field production flexibility," Energy, Elsevier, vol. 252(C).
    3. Hong, Bingyuan & Li, Xiaoping & Song, Shangfei & Chen, Shilin & Zhao, Changlong & Gong, Jing, 2020. "Optimal planning and modular infrastructure dynamic allocation for shale gas production," Applied Energy, Elsevier, vol. 261(C).
    4. Tan, Siah Hong & Barton, Paul I., 2015. "Optimal dynamic allocation of mobile plants to monetize associated or stranded natural gas, part I: Bakken shale play case study," Energy, Elsevier, vol. 93(P2), pages 1581-1594.
    5. Shakibi, Hamid & Shokri, Afshar & Assareh, Ehsanolah & Yari, Mortaza & Lee, Moonyong, 2023. "Using machine learning approaches to model and optimize a combined solar/natural gas-based power and freshwater cogeneration system," Applied Energy, Elsevier, vol. 333(C).
    6. Wang, Xucen & Li, Min & Cai, Liuxi & Li, Yun, 2020. "Propane and iso-butane pre-cooled mixed refrigerant liquefaction process for small-scale skid-mounted natural gas liquefaction," Applied Energy, Elsevier, vol. 275(C).
    7. Verma, Nishant Kumar & Chatterjee, Ashish K., 2023. "Process flexibility in the presence of product modularity: Does modularity help?," International Journal of Production Economics, Elsevier, vol. 256(C).
    8. Huang, Renxing & Kang, Lixia & Liu, Yongzhong, 2022. "Renewable synthetic methanol system design based on modular production lines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    9. Mignacca, Benito & Locatelli, Giorgio & Velenturf, Anne, 2020. "Modularisation as enabler of circular economy in energy infrastructure," Energy Policy, Elsevier, vol. 139(C).
    10. Hsieh, Tsung-Jung, 2023. "Performance indicator-based multi-objective reliability optimization for multi-type production systems with heterogeneous machines," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    11. Tan, Siah Hong & Barton, Paul I., 2016. "Optimal dynamic allocation of mobile plants to monetize associated or stranded natural gas, part II: Dealing with uncertainty," Energy, Elsevier, vol. 96(C), pages 461-467.
    12. Kong, Fulin & Liu, Yuxin & Tong, Lige & Guo, Wei & Qiu, Yinan & Wang, Li, 2022. "Optimization of co-production air separation unit based on MILP under multi-product deterministic demand," Applied Energy, Elsevier, vol. 325(C).
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